Who we are

• Five partner universities

  • UK Data Archive, University of Essex (lead partner)
  • Cathie Marsh Institute, University of Manchester
  • Jisc, University of Manchester
  • EDINA, University of Edinburgh
  • University College London

• 100+ staff

• Exists as UKDS since 2012 (as UKDA 1967)

• National data since 2003

What we do

• The main single point of access for UK social science data
• Secondary data collection, curation and access
• Training and user support
• Communication and user engagement
• Impact
• … Key part of the UK social science research infrastructure, funded by the UKRI/ESRC

Our data…

• UK social survey microdata:

  • Cross-sectional: large government and academic surveys
  • Longitudinal: major studies following people over time

• Multinational data: survey data, aggregate databases
  

• Census tables and individual data – current and historical

• Business microdata and administrative data

• Qualitative data: multimedia files and interview transcripts

What do we mean by ‘data’ (1)

• Individual vs aggregated
• Nature of data: survey vs other source: devices, administrative records, etc.
• About organisations (ie schools) vs people
• From organisations and young people
• One off studies vs series
• Photography (ie cross-sectional) vs video (longitudinal)
• Our focus today: individual survey microdata

What do we mean by ‘data’ (2)

• Questions asked to people

  • About objective characteristics ie height, weight, age

  • About views and attitude:

    • Attitudes and opinions on crime, gender change
    • Validated instruments (ie mental health)

• External measurement (biosample, genetic, cortisol levels)

• Smart data (from devices ex accelerometer, energy meter)

• Linked administrative records - more on this later

Education-related questions (MCS)

• Qualifications (academic/vocational):
  • Type; level; grade, subject
• Current education:
  • where studying; year; school moves; whether fees-paying
  • qualifications studying for: type; number; subjects
• Are studies/training choices informed by job wishes to do
• From whom obtained post-16 educational advice
• The Strengths and Difficulties Questionnaire

At a glance …

• (Birth) cohort studies
• Understanding Society
• Census
• Linked data
• A few repeated cross-sectional studies

Birth cohort studies

• Follow a sample of individuals from birth until death
• People born during during the same specific period of time in 1958(NCDS), 1970(BCS), 2000 (MCS), 2026 (Generation New Area)
• Wide range of measurements, including education and health
• Within and between cohort analysis
• Managed by the Centre for Longitudinal Studies (UCL)

The Cohort Studies at the CLS

Millennium Cohort Study (MCS)

• ~ 19K children (born between June 2001 and Jan 2003)
• 8 sweeps: age 9 months then 3, 5, 7, 11, 14, 17, 23
• Parent and child interviews
• Education, skills, health, truancy, cognitive ability…
• Biological measurements
• … Socio-economic and demographic characteristics
• Data available at the UK Data Service here

Example: Kandola et al (2022)

• Screen-based sedentary behaviour and depression

  • Is a sedentary lifestyle alongside screen and device usage, associated with depression?
  • Does physical activity make a difference?

• 11,341 teenagers from the Millennium Cohort Study

• The main outcome was depressive symptoms at age 14

  • A measured by the Moods and Feelings questionnaire

• Against frequency of video game, social media, and internet use (age 11).

• Impact of self-reported physical activity

Results

• IRR: likelihood of depression (\(<1=\)less likely, \(>1=\)more likely)

Conclusions

• More frequent gaming at age 11 associated with a lower risk of depressive symptoms at age 14 for boys but not girls.
• More frequent social media use at 11 associated with a higher risk of depressive symptoms in girls but not boys.
• More frequent video game use was consistently associated with fewer depressive symptoms for boys with low physical activity, but not those with high physical activity

Next Steps

• 16,000 people born in 1989-90 followed from age 13-14
• Annual sweeps between ages 14-20, then 25 and 32
• Oversampling of ethnic minorities and deprived schools
• Covers educational attainment and aspirations, health and well-being, and social attitudes
• Linked administrative data available
• Transitions from secondary to post-16 and higher education, family formation, housing, and early labour market entry
• Available at the UK Data Service

Next Steps on the CLS website

Growing Up in Scotland

• Large-scale, Scottish cohort study (Website)
• Cohort 1:
  • A sample of children born in 2005-6
  • 11 yearly sweeps. Most recent is Sweep 11 (Age 17-18)
  • 5,217 children at Sweep 1 —> 2,469 at sweep 11
• Cohort 2
  • a sample of children aged around 10 months in 2011.
  • 3 sweeps, most recentis Sweep 3 (Age 5 )
  • 6,127 at Sweep 1 —> 4,434 at Sweep 5
• Growing up in Scotland Series at the UK Data Service

GuS Data and variables

• Mental health: depression, Strengths and Difficulties Questionnaire)

• Diet and sleep; Alcohol consumption, smoking, drug use

• Anti-social behaviour and offending

• Parent physical and mental health

• Linked data

  • Sweep 11 school attainment records - using Scottish Candidate Numbers
  • Sweep 8 Recorded physical activity data

Understanding Society

• Largest longitudinal study of the UK population

• 40K households, 100K individuals initially (2009)

• 17 waves so far: 2009-23. Includes BHPS data 1991-2009

• Ethnic minority boost samples, innovation panel

• Very wide range of topics covered:

  • Employment, income, benefits, savings, debt, and assets
  • Health, well-being, and health behaviour
  • Housing, housing costs, and dwelling characteristics

Young people in Understanding Society

• Youth (ie 10-15yo) self-completion questionnaire
• Usage of smarphone and devices
• Online vs in person socialising
• Usage of apps
• Family support, athmosphere and trust
• Strength and Difficulties questionnaire; self-image
• View about education; schoolwork and bullying

Young people and mental health (1)

Parra-Mujica, Johnson et al (2023)

• Positive association between health for the 16 to 24 and:

  • differences in household income
  • short-term income changes are significant,

• Microsimulation shows that respondents on lower income would benefit the most from increases in their income,

• Focusing on the poorest risks neglecting other vulnerable subgroups, ie young workers and single youth

Young people and mental health (2)

Linked administrative datasets

• Records produced when a survey respondent interacts a government organisation

  • hospitalisation, sitting an exam, becoming an employee

• Can be merged with survey data…

  • Where prior consent was obtained from respondents

• Entails more stringent conditions of access (Secure access)

• Early days, especially for everyday users but expanding area

Linked data examples

• Understanding Society:
  • Scottish Education Data 2007-2018
  • National Pupil Database (England)
• Millennium Cohort Study
  • Distances to English Grammar Schools, 2012
  • Distances to Current, 1st, 2nd, and 3rd Choice Schools
• Next Steps:
  • Student Loans Company Records 2007-202
  • Individualised Learner Records

Census records

• Fine grained socio-demographic population estimates

• By age group:

  • Deprivation
  • Economic activity
  • Educational status
  • Ethnicity
  • Disability

• Typical application: population estimates for small areas

Residents aged 0-24 as a % of the population by LSOAs , 2021

.

Source

Young People and Gambling Survey

• Attitudes towards and participation in different types of gambling activities

  • Legal and age restricted gambling

• Data controller: Gambling Commission.

• 3,666 pupils aged 11 to 17 yo (school years 7 to 12 (S1 to S6 in Scotland

• You can find it here

Qualitative & deposited research data

• No qualitative equivalent to the major quantitative studies but…
• ESRC grantholders are required to deposit their data
• A growing treasure trove of qualitative (and quantitative ) research data on various topics, including young people
• Often freely accessible via ReShare on the UKDS website, data owner authorisation is sometimes required

The main UKDS data catalogue page

How to access safeguarded data

• Register with the UK Data Service

  • Slightly differences for UK academic users and other users

• Create a project (‘non commercial’, ‘commercial’, ‘teaching’)

• Search, find and order the data

• Add it to your project

• Download it…

• Et voilà.

• The steps to follow are detailed on our website

Other levels of access

• Open data: can be downloaded without registration

• ReShare data (ie deposited) data: conditions will depend on the data owner; most of the time freely downloadable

• Controlled data:

  • Register
  • Provide a detailed description of your project
  • Apply for Safe Researcher certification
  • Follow the Safe Researcher training
  • Access the data via the SecureLab - ie secure VPN from an institutional computer

Essential questions to ask yourself

• Data quality
  • What was the phrasing of the question(s)?
  • What was the research question/funder of the research?
  • Is it representative, is the sample size large enough, what is the population of reference?
  • When was it collected?
  • Is the documentation – technical report available?
  • Are weights and survey design information provided?
• Is a special application required in order to access the data?

Take aways

• Wealth of data on young people and education
• From surveys and beyond
• Education and other relevant topics
• Different ways of searching
• Different levels of access